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An improved exponential metric space approach for C‐mean clustering analysing.
- Source :
-
Expert Systems . May2024, Vol. 41 Issue 5, p1-15. 15p. - Publication Year :
- 2024
-
Abstract
- In this article, we present two resilient algorithms, the improved alternative hard c‐means (IAHCM) and the improved alternative fuzzy c‐means (IAFCM). We implement the Gaussian distance‐dependent function proposed by Zhang and Chen (D.‐Q. Zhang and Chen, 2004). In some cases, Zhang and Chen's metric distance does not account for the clustering centroid effect predicted by the large value. R* is employed in IAHCM and IAFCM to discover robust results while minimizing its sensitivity. Experiments are conducted using two‐and three‐dimensional data, including Diamond and Iris real‐world data. The results are based on demonstrating the robust simplicity and applicability of the offered algorithms. Similarly, computational complexity is assessed. [ABSTRACT FROM AUTHOR]
- Subjects :
- *CENTROID
*GAUSSIAN function
*COMPUTATIONAL complexity
*METRIC spaces
*ALGORITHMS
Subjects
Details
- Language :
- English
- ISSN :
- 02664720
- Volume :
- 41
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- Expert Systems
- Publication Type :
- Academic Journal
- Accession number :
- 176451510
- Full Text :
- https://doi.org/10.1111/exsy.12896